Researchers from the Brigham Young University have developed a model that precisely characterises the material in each pixel of an image taken from a long-wave infrared camera.
The method could help detect and describe potentially dangerous materials from a distance, researchers said.
The project was funded by the US National Nuclear Security Administration through a grant awarded to BYU engineering professor Gustavious Williams.
The US government's long-term goal for infrared technology is to remotely detect the exact materials, chemicals and gases coming and going from factories or other sites suspected of illegal nuclear production.
Infrared cameras capture wavelengths of light that are not visible to the human eye. Hyper-spectral infrared cameras capture this light in hundreds of narrow bands.
Since different materials reflect or absorb different bands of light, scientists can characterise the materials by analysing the picture.
Identification of materials would be straightforward if those were the only signals bouncing back at the camera. But other incoming signals, such as the object's temperature and the weather conditions, muddle the analysis and add noise to the material's light signature.
"What we wanted to know is if you didn't know anything about the material in an image, and we had a number of pictures over time, could we let the algorithms figure out what the different materials are and separate them out," Williams said.
The resulting information is more akin to measuring the material with a spectrometer in a lab. Berrett's model can also group together pixels that are related to each other to map out the various materials in an image.
"As the technique develops, this could do much more than spot a bomb-making plant. Imagine taking an infrared picture from above a city struck by an earthquake or tornado," researchers said.
"In addition to spotting all the gas leaks, it could reveal the exact gases being leaked and their concentrations in different neighbourhoods," they said.
The study was published in the journal Technometrics.
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